Conceptual design of bicycle frames by multiobjective shape annealing

Suppapitnarm, A; Parks, GT; Shea, Kristina; Clarkson, P. John

doi:10.1080/03052150310001633214

Cited by 17 publications

(8 citation statements)

References 24 publications

(28 reference statements)

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“…In this example, we can see that the given design domain affects the computed final structure, and our proposed framework can handle both concave and convex domains without any modifications to the design method. Figure 18 shows a test case using a bicycle frame structure [44]. The given load simulates the situation of a person sitting on the frame and holding the front handles.…”

Section: L-shaped Design Domainmentioning

confidence: 99%

A structural topology design method based on principal stress line

Kwok

2016

Computer-Aided Design

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Topology optimization is an important topic in structural mechanics. One common application is to obtain the optimal distribution of material that maximizes the stiffness of the solution (minimize the compliance). However, as an iterative process, topology optimization of large and complex structures is computationally intensive. The problem becomes even more complicated if the manufacturing constraints are taken into account in the optimization process. In this paper, a novel growth method based on principal stress lines (PSLs) is presented for topology optimization. The PSLs are traced in the design domain along the direction of principal stresses, in which the materials would be located to define the geometry and topology of the structure. Consequently, the optimization problem is converted into a geometric design problem. Compared to previous methods, the computation based on PSLs is fast, and the designer can have explicit control over the number of structural members. In addition, the manufacturing constraints can easily be incorporated. Multiple test cases are given to illustrate the presented method. The PSL-based method is promising for building practical designing tools for various structural applications.

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Section: L-shaped Design Domainmentioning

confidence: 99%

A structural topology design method based on principal stress line

Kwok

2016

Computer-Aided Design

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“…This set of move operators is not designed to constitute a rigorous design grammar, such as those developed for computational synthesis of frame and truss structures [92,93]. Rather, this set of move operators is designed to reflect the operations available to human participants through the design GUI during the cognitive study (MO1-6), and also to allow simple heuristic combinations of operations (MO7-8).…”

Section: Mo8 Add a Joint And Attachmentioning

confidence: 99%

Designing the Characteristics of Design Teams via Cognitively Inspired Computational Modeling

McComb¹

2018

Preprint

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Teams are a ubiquitous part of the design process and a great deal of time and effort is devoted to managing them effectively. Although teams have the potential to search effectively for solutions, they are also prone to a number of pitfalls. Thus, a greater understanding of teams is necessary to ensure that they can function optimally across a variety of tasks. Teams are typically studied through controlled laboratory experiments or through longitudinal studies that observe teams in situ. However, both of these study types can be costly and time-consuming. Months, if not years, pass between the initial conception of a study and the final analysis of results. This work creates a computational framework that efficiently emulates human design teams, thus facilitating the derivation of a theory linking the properties of design problems to optimized team characteristics, effectively making it possible to design design teams.This dissertation first introduces and validates the Cognitively-Inspired Simulated Annealing Teams (CISAT) modeling framework. The central structure of CISAT is modeled after simulated annealing, a global optimization algorithm that has been shown to effectively mimic the problem-solving process of individuals. Specifically, a multi-agent analog of simulated annealing is used in CISAT to mimic the behavior of teams. Several additional components, drawn from the psychology and problem-solving literature, are then included in the framework to enable a more accurate description of individual activity and interaction within the team. CISAT is then used to investigate the relationship between design problem properties, team characteristics, and task performance. Multiple computational simulations are conducted in which simulated teams with various characteristics solve a variety of different configuration problems. These simulations are then post-processed to produce a set of equations that make it possible to predict optimal team characteristics based on problem properties, thus enabling the optimal design of design teams. To validate these equations a behavioral study is designed and conducted in which teams of engineering students interact at different frequencies while designing a complex system. Results of the study offer a limited validation of the predictive equations.This dissertation further highlights the resource efficiency and versatility of CISAT by demonstrating its use in two additional applications. In the first, a new numerical optimization algorithm is derived directly from CISAT by stripping away all but the most quintessential team-based characteristics. The team-based characteristics of this algorithm allow it to achieve high performance across a variety of objective function with diverse topographies. In the second application, CISAT is used in conjunction with Markov concepts to examine the order in which designers make changes to their solutions. Although it has been demonstrated that humans apply changes in a specific order (called a sequence) when solving puzzles, such patterns have not been examined for engineers solving design problems. It is shown that operation sequences are used by designers, and improve solution quality. This dissertation demonstrates how characteristics of individual designers and design teams can be captured and accurately reproduced within a computational model to advance our knowledge of design methodology. Future extensions of this work have the potential to inform a deeper and more holistic understanding of the search process.

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“…The shape annealing method integrates shape rules with the FEM, along with a simulated annealing algorithm to generate various structural designs that satisfy certain objectives and constraints (Shea & Cagan, 1997, 1999; Shea et al, 1997). Most of its rules can be represented with the subdivision schema x → div( x ), while others have addition, transformation, and erasing schemas: x → t ( x ); x → x + t ( x ); x →, including their inversed version: a → b and b → a (Suppapitnarm et al, 2004). While deriving various topological variants, the rules are able to preserve a certain design language.…”

Section: Parametric and Grammatical Structure Revisitedmentioning

confidence: 99%